Edward Hughes (Google DeepMind) to speak at RAAIS 2025
On open-endedness as a path to AGI.
The Research and Applied AI Summit (RAAIS) is a community for entrepreneurs and researchers who accelerate the science and applications of AI technology. In the run up to our 9th annual event on June 13th 2025 in London, we’re running a series of speaker profiles to shed more light on what you can expect to learn on the day!
Edward is a Staff Research Engineer at Google DeepMind, a Visiting Fellow at the London School of Economics, an Advisor to the Cooperative AI Foundation, and a PIBBSS mentor. He received his PhD in Theoretical Physics from Queen Mary University of London on applications of string theory to particle scattering.
Edward is a scientific leader in the field of AI with a particular focus on open-ended systems. His teams have pioneered fast adaptation in reinforcement learning, the paradigm of Cooperative AI, and ad-hoc collaboration between machines and humans. Edward is a generalist, equally passionate about science, engineering and leadership. He draws inspiration from diverse sources, including ethics, cultural evolution, social psychology, economics, organisational design, and meta-learning. He is happiest driving rapid, measurable progress on high-risk, high-impact projects.
At DeepMind, Edward’s work sits at the intersection of cutting-edge research and ambitious, practical implementation. His recent focus includes building agents capable of zero-shot cooperation with humans and machines—work that pushes the boundaries of multi-agent systems and aligns closely with real-world deployment challenges. He brings a systems-level perspective to the future of AI, one that integrates technical excellence with deep questions about alignment, generalisation, and societal impact.
Outside the lab, Edward is known for mentoring emerging researchers and shaping the field of Cooperative AI, an area gaining urgency as AI systems become increasingly autonomous and socially embedded. His ability to operate across technical domains—from deep reinforcement learning to theoretical physics—gives him a rare vantage point on how general intelligence might be built and governed.
At RAAIS, Edward will speak to both the technical core and philosophical edge of AI research: how to build systems that are not only intelligent, but collaborative, adaptive, and aligned with human values in complex environments.